Recent and future distribution of the alien Chinese pond mussel Sinanodonta woodiana (Lea, 1834) on the European continent

Abstract

The alien freshwater mussel Sinanodonta woodiana (Lea, 1834) has rapidly spread throughout Europe over the past decades. This species can cope with a broad range of environmental conditions and has a high reproductive capacity making S. woodiana a successful invader. Due to its negative effects on native freshwater mollusk communities and parasitized fish it is critical to identify suitable habitats where S. woodiana may persist and how these habitats may be altered under future climate projections. We applied multivariate ordination methods to analyze the space-time relationship and a maximum entropy approach (MaxEnt) to predict the recent (1970–2000) and future (2041–2060 and 2081–2100) distribution of S. woodiana using environmental and climate variables for the European continent. After first sightings in 1979 there were only a few new locations and findings which increased unevenly and exponentially to a maximum of about 100 new locations per year followed by decline during the last few years. Under recent climate condition, 2.3% of European watersheds are predicted as highly suitable habitat for S. woodiana and located in the temperate climate zone between 40°N and 60°N. Suitable habitat was associated with lowland watersheds characterized by fluviatile deposits and agriculture. Elevation, the distance between water bodies, land cover and mean temperature of the coldest quarter were the main factors influencing the modeling results. For future climate scenarios, highly suitable habitat increased to 2.4% by the middle of this century and decreased to 2.2% by the end of the century under the ‘least radiative forcing’ scenario. For the intermediate and high radiative forcing in 2050 and 2100, highly suitable habitat decreased to 2.2% and 1.7% and to 2.2% and 2.2%, respectively. Results from our study can be used as a baseline to better understand potential invasion pathways, identify high risk areas, and to initiate early detection and rapid response strategies.